Triple

T1991254
Position Surface form Disambiguated ID Type / Status
Subject Zamoskvoretskaya Line E43255 entity
Predicate hasStation P35 FINISHED
Object Orekhovo
Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
 E248635 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Orekhovo | Statement: [Zamoskvoretskaya Line, hasStation, Orekhovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orekhovo
Context triple: [Zamoskvoretskaya Line, hasStation, Orekhovo]
  • A. Noginsk
    Noginsk is a town in western Russia that serves as an industrial and transport center east of Moscow.
  • B. Terekhovo
    Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
  • C. Ramenskoye
    Ramenskoye is a town in Moscow Oblast, Russia, located southeast of Moscow and known for its industrial base and proximity to major Moscow airports.
  • D. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • E. Novo-Ogaryovo
    Novo-Ogaryovo is a suburban governmental estate outside Moscow that serves as one of the primary official residences of Russian President Vladimir Putin.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Orekhovo
Triple: [Zamoskvoretskaya Line, hasStation, Orekhovo]
Generated description
Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orekhovo
Target entity description: Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
  • A. Noginsk
    Noginsk is a town in western Russia that serves as an industrial and transport center east of Moscow.
  • B. Terekhovo
    Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
  • C. Ramenskoye
    Ramenskoye is a town in Moscow Oblast, Russia, located southeast of Moscow and known for its industrial base and proximity to major Moscow airports.
  • D. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • E. Novo-Ogaryovo
    Novo-Ogaryovo is a suburban governmental estate outside Moscow that serves as one of the primary official residences of Russian President Vladimir Putin.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a88714cf2c819081644be450b8356e completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8451fe8819093531052f4533c36 completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6ae66fe08190be75c18f0916f23b completed March 9, 2026, 6:38 a.m.
NEDg Description generation batch_69ae6b9da51c819085beb79a14f5d8b5 completed March 9, 2026, 6:41 a.m.
NED2 Entity disambiguation (via description) batch_69ae6c2a465c8190a9fe2a465e9ac3f0 completed March 9, 2026, 6:43 a.m.
Created at: March 4, 2026, 7:37 p.m.